Animal Infectious Diseases Prevention through Big Data and Deep Learning (빅데이터와 딥러닝을 활용한 동물 감염병 확산 차단)
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- Journal of Intelligence and Information Systems
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- v.24 no.4
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- pp.137-154
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- 2018
Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.
As relationship between buyer and seller has been brought closer and long-term relationship has been more important in B2B markets, the importance of service and service convenience increases as well as product. In homogeneous markets, where service offerings are similar and therefore not key competitive differentiator, providing greater convenience may enable a competitive advantage. Service convenience, as conceptualized by Berry et al. (2002), is defined as the consumers' time and effort perceptions related to buying or using a service. For this reason, B2B customers are interested in how fast the service is provided and how much save non-monetary cost like time or effort by the service convenience along with service quality. Therefore, this study attempts to investigate the impact of service convenience on relationship factors such as relationship satisfaction, relationship commitment, and relationship performance. The purpose of this study is to find out whether service convenience can be a new antecedent of relationship quality and relationship performance. In addition, this study tries to examine how five-dimensional service convenience constructs (decision convenience, access convenience, transaction convenience, benefit convenience, post-benefit convenience) affect customers' relationship satisfaction, relationship commitment, and relationship performance. The service convenience comprises five fundamental components - decision convenience (the perceived time and effort costs associated with service purchase or use decisions), access convenience(the perceived time and effort costs associated with initiating service delivery), transaction convenience(the perceived time and effort costs associated with finalizing the transaction), benefit convenience(the perceived time and effort costs associated with experiencing the core benefits of the offering) and post-benefit convenience (the perceived time and effort costs associated with reestablishing subsequent contact with the firm). Earlier studies of perceived service convenience in the industrial market are none. The conventional studies that have dealt with service convenience have usually been made in the consumer market, or they have dealt with convenience aspects in the service process. This service convenience measure for consumer market can be useful tool to estimate service quality in B2B market. The conceptualization developed by Berry et al. (2002) reflects a multistage, experiential consumption process in which evaluations of convenience vary at each stage. For this reason, the service convenience measure is good for B2B service environment which has complex processes and various types. Especially when categorizing B2B service as sequential stage of service delivery like Kumar and Kumar (2004), the Berry's service convenience measure which reflect sequential flow of service deliveries suitable to establish B2B service convenience. For this study, data were gathered from respondents who often buy business service and analyzed by structural equation modeling. The sample size in the present study is 119. Composite reliability values and average variance extracted values were examined for each variable to have reliability. We determine whether the measurement model supports the convergent validity by CFA, and discriminant validity was assessed by examining the correlation matrix of the constructs. For each pair of constructs, the square root of the average variance extracted exceeded their correlations, thus supporting the discriminant validity of the constructs. Hypotheses were tested using the Smart PLS 2.0 and we calculated the PLS path values and followed with a bootstrap re-sampling method to test the hypotheses. Among the five dimensional service convenience constructs, four constructs (decision convenience, transaction convenience, benefit convenience, post-benefit convenience) affected customers' positive relationship satisfaction, relationship commitment, and relationship performance. This result means that service convenience is important cue to improve relationship between buyer and seller. One of the five service convenience dimensions, access convenience, does not affect relationship quality and performance, which implies that the dimension of service convenience is not important factor of cumulative satisfaction. The Cumulative satisfaction can be distinguished from transaction-specific customer satisfaction, which is an immediate post-purchase evaluative judgment or an affective reaction to the most recent transactional experience with the firm. Because access convenience minimizes the physical effort associated with initiating an exchange, the effect on relationship satisfaction similar to cumulative satisfaction may be relatively low in terms of importance than transaction-specific customer satisfaction. Also, B2B firms focus on service quality, price, benefit, follow-up service and so on than convenience of time or place in service because it is relatively difficult to change existing transaction partners in B2B market compared to consumer market. In addition, this study using partial least squares methods reveals that customers' satisfaction and commitment toward relationship has mediating role between the service convenience and relationship performance. The result shows that management and investment to improve service convenience make customers' positive relationship satisfaction, and then the positive relationship satisfaction can enhance the relationship commitment and relationship performance. And to conclude, service convenience management is an important part of successful relationship performance management, and the service convenience is an important antecedent of relationship between buyer and seller such as the relationship commitment and relationship performance. Therefore, it has more important to improve relationship performance that service providers enhance service convenience although competitive service development or service quality improvement is important. Given the pressure to provide increased convenience, it is not surprising that organizations have made significant investments in enhancing the convenience aspect of their product and service offering.
As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.
The basic purpose of this study is to investigate perceived quality and service personal value affecting the result of long-term relationship between service buyers and suppliers. This research presented a constructive model(perceived quality affecting the service personal value and the moderate effect of NFC) in the on off line and then propose the research model base on prior researches and studies about relationships among components of service. Data were gathered from respondents who visit at the education service market. For this study, Data were analyzed by AMOS 7.0. We integrate the literature on services marketing with researches on personal values and perceived quality. The SERPVAL scale presented here allows for the creation of a common ground for assessing service personal values, giving a clear understanding of the key value dimensions behind service choice and usage. It will lead to a focus of future research in services marketing, extending knowledge in the field and stimulating further empirical research on service personal values. At the managerial level, as a tool the SERPVAL scale should allow practitioners to evaluate and improve the value of a service, and consequently, to define strategies and actions to address services for customers based on their fundamental personal values. Through qualitative and empirical research, we find that the service quality construct conforms to the structure of a second-order factor model that ties service quality perceptions to distinct and actionable dimensions: outcome, interaction, and environmental quality. In turn, each has two subdimensions that define the basis of service quality perceptions. The authors further suggest that for each of these subdimensions to contribute to improved service quality perceptions, the quality received by consumers must be perceived to be reliable, responsive, and empathetic. Although the service personal value may be found in researches that explore individual values and their consequences for consumer behavior, there is no established operationalization of a SERPVAL scale. The inexistence of an established scale, duly adapted in order to understand and analyze personal values behind services usage, exposes the need of a measurement scale with such a purpose. This need has to be rooted, however, in a conceptualization of the construct being scaled. Service personal values can be defined as a customer's overall assessment of the use of a service based on the perception of what is achieved in terms of his own personal values. As consumer behaviors serve to show an individual's values, the use of a service can also be a way to fulfill and demonstrate consumers'personal values. In this sense, a service can provide more to the customer than its concrete and abstract attributes at both the attribute and the quality levels, and more than its functional consequences at the value level. Both values and services literatures agree, that personal value is the highest-level concept, followed by instrumental values, attitudes and finally by product attributes. Purchasing behaviors are agreed to be the end result of these concepts' interaction, with personal values taking a major role in the final decision process. From both consumers' and practitioners' perspectives, values are extremely relevant, as they are desirable goals that serve as guiding principles in people's lives. While building on previous research, we propose to assess service personal values through three broad groups of individual dimensions; at the self-oriented level, we use (1) service value to peaceful life (SVPL) and, at the social-oriented level, we use (2) service value to social recognition (SVSR), and (3) service value to social integration (SVSI). Service value to peaceful life is our first dimension. This dimension emerged as a combination of values coming from the RVS scale, a scale built specifically to assess general individual values. If a service promotes a pleasurable life, brings or improves tranquility, safety and harmony, then its user recognizes the value of this service. Generally, this service can improve the user's pleasure of life, since it protects or defends the consumer from threats to life or pressures on it. While building upon both the LOV scale, a scale built specifically to assess consumer values, and the RVS scale for individual values, we develop the other two dimensions: SVSR and SVSI. The roles of social recognition and social integration to improve service personal value have been seriously neglected. Social recognition derives its outcome utility from its predictive utility. When applying this underlying belief to our second dimension, SVSR, we assume that people use a service while taking into consideration the content of what is delivered. Individuals consider whether the service aids in gaining respect from others, social recognition and status, as well as whether it allows achieving a more fulfilled and stimulating life, which might then be revealed to others. People also tend to engage in behavior that receives social recognition and to avoid behavior that leads to social disapproval, and this contributes to an individual's social integration. This leads us to the third dimension, SVSI, which is based on the fact that if the consumer perceives that a service strengthens friendships, provides the possibility of becoming more integrated in the group, or promotes better relationships at the social, professional or family levels, then the service will contribute to social integration, and naturally the individual will recognize personal value in the service. Most of the research in business values deals with individual values. However, to our knowledge, no study has dealt with assessing overall personal values as well as their dimensions in a service context. Our final results show that the scales adapted from the Schwartz list were excluded. A possible explanation is that although Schwartz builds on Rokeach work in order to explore individual values, its dimensions might be especially focused on analyzing societal values. As we are looking for individual dimensions, this might explain why the values inspired by the Schwartz list were excluded from the model. The hierarchical structure of the final scale presented in this paper also presents theoretical implications. Although we cannot claim to definitively capture the dimensions of service personal values, we believe that we come close to capturing these overall evaluations because the second-order factor extracts the underlying commonality among dimensions. In addition to obtaining respondents' evaluations of the dimensions, the second-order factor model captures the common variance among these dimensions, reflecting the respondents' overall assessment of service personal values. Towards this fact, we expect that the service personal values conceptualization and measurement scale presented here contributes to both business values literature and the service marketing field, allowing for the delineation of strategies for adding value to services. This new scale also presents managerial implications. The SERPVAL dimensions give some guidance on how to better pursue a highly service-oriented business strategy. Indeed, the SERPVAL scale can be used for benchmarking purposes, as this scale can be used to identify whether or not a firms' marketing strategies are consistent with consumers' expectations. Managerial assessment of the personal values of a service might be extremely important because it allows managers to better understand what customers want or value. Thus, this scale allows us to identify what services are really valuable to the final consumer; providing knowledge for making choices regarding which services to include. Traditional approaches have focused their attention on service attributes (as quality) and service consequences(as service value), but personal values may be an important set of variables to be considered in understanding what attracts consumers to a certain service. By using the SERPVAL scale to assess the personal values associated with a services usage, managers may better understand the reasons behind services' usage, so that they may handle them more efficiently. While testing nomological validity, our empirical findings demonstrate that the three SERPVAL dimensions are positively and significantly associated with satisfaction. Additionally, while service value to social integration is related only with loyalty, service value to peaceful life is associated with both loyalty and repurchase intent. It is also interesting and surprising that service value to social recognition appears not to be significantly linked with loyalty and repurchase intent. A possible explanation is that no mobile service provider has yet emerged in the market as a luxury provider. All of the Portuguese providers are still trying to capture market share by means of low-end pricing. This research has implications for consumers as well. As more companies seek to build relationships with their customers, consumers are easily able to examine whether these relationships provide real value or not to their own lives. The selection of a strategy for a particular service depends on its customers' personal values. Being highly customer-oriented means having a strong commitment to customers, trying to create customer value and understanding customer needs. Enhancing service distinctiveness in order to provide a peaceful life, increase social recognition and gain a better social integration are all possible strategies that companies may pursue, but the one to pursue depends on the outstanding personal values held by the service customers. Data were gathered from 284 respondents in the korean discount store and online shopping mall market. This research proposed 3 hypotheses on 6 latent variables and tested through structural equation modeling. 6 alternative measurements were compared through statistical significance test of the 6 paths of research model and the overall fitting level of structural equation model. and the result was successful. and Perceived quality more positively influences service personal value when NFC is high than when no NFC is low in the off-line market. The results of the study indicate that service quality is properly modeled as an antecedent of service personal value. We consider the research and managerial implications of the study and its limitations. In sum, by knowing the dimensions a consumer takes into account when choosing a service, a better understanding of purchasing behaviors may be realized, guiding managers toward customers expectations. By defining strategies and actions that address potential problems with the service personal values, managers might ultimately influence their firm's performance. we expect to contribute to both business values and service marketing literatures through the development of the service personal value. At a time when marketing researchers are challenged to provide research with practical implications, it is also believed that this framework may be used by managers to pursue service-oriented business strategies while taking into consideration what customers value.